Barr: Gene expression profiling is the measurement of the simultaneous activity, or expression, of the approximately 25,000 genes of the human genome. This technique provides a quantitative measure of the amount of messenger RNA (mRNA) transcripts present for all of the probes (genes) present on the chosen microarray across cases and controls. Gene expression profiling is a powerful and effective approach to identifying genes, pathways, and interactions correlated with a phenotype, and the technology has also been used to identify genes and gene interactions for the prediction of a phenotype. Gene expression profiling is commonly done with microarray experiments in which the expression of thousands of genes is compared in two groups of people, one with the disease in question and one without it. Serial analysis of gene expression (SAGE) is a similar approach; however, it does not rely on known sequence information, as does microarray. Therefore one can obtain novel gene profiles from poorly characterized genomic sequences using SAGE.

AAN.com: Describe the objectives and methodology of your study.

Barr: We wanted to assess the profile of genes expressed in the first 24 hours after a stroke, and to validate the findings of recent study in which Frank Sharp, MD, and his colleagues identified 18 genes, most of them related to the inflammatory response, associated with acute stroke. In our study we looked at patients with definite acute ischemic cerebrovascular syndrome (AICS) who had blood drawn within 24 hours of the time when they were last known normal. Because we wanted to identify a genetic profile of the response to stroke rather than the presence of risk factors for stroke, our control population was matched to our patients based on the presence of comorbidities such as age, hyptertension and hyperlipidemia. We extracted RNA from whole blood and used it to produce complementary DNA (cDNA). We measured the amount of cDNA produced for that gene to determine which genes were the most highly expressed in patients with stroke. Using this technique, we identified a 9-gene panel specific for ischemic stroke.

AAN.com: Presumably, the time when you draw the blood is critical, because different genes are expressed at different times after a stroke. When did you draw the blood?

Barr: The blood was drawn while the patients were undergoing the acute evaluation for stroke in the ED, and they had to be within 24 hours from the time when they were last known to be without stroke symptoms. The mean time to blood draw in our study was around 10 hours (the range was 3 to 22 hours). We chose this time window because most stroke patients seek care in the first 24 hours, and we wanted to evaluate the immediate response to stroke.

AAN.com: Which genes did you identify?

Barr: We identified 8 genes that were upregulated in the peripheral blood with ≥ 2 fold difference in expression between cases and controls following ischemic stroke: Arginase 1 (ARG1); carbonic anhydrase 4 (CA4); chondroitin sulfate proteoglycan 2 (CSPG2); IG motif-containing GTPase activation protein 1 (IQGAP1); lymphocyte antigen 96 (LY96); matrix metalloproteinase 9 (MMP9); orosomucoid 1 (ORM1) and s100 calcium binding protein A12 (s100A12). We also found one gene that was down-regulated: chemokine receptor 7 (CCR7). The changes in the expression of CCR7, IQGAP1, and ORM1 had not been previously identified. There are several reasons why were able to identify the expression of these genes: we enrolled a large sample in our study (39 stroke patients and 24 controls), our sample was racially homogenous (all were Caucasian), and we used a different microarray platform than earlier studies. We are confident that these new genes are associated with stroke because we chose to conduct strict significance testing which included Bonferroni correction for multiple testing and comparison between two statistical software packages, to decrease the number of false positive associations. However, our findings need to be replicated in future studies.

AAN.com: What are the processes mediated by the genes you identified, and why do you speculate they are expressed at the time?

Barr: Most of the genes in the 9-gene panel are involved in the innate immune system response to damage signals (e.g., increased stress). In addition, Ingenuity Systems pathway analysis (IPA) identified Toll like receptor 4 (TLR4) signaling as the most significant for our dataset. IPA is a bioinformatic tool used to model and understand complex biological systems and give meaning to microarray data from a systems perspective. Activation of innate immunity, through TLRs, is a primary component of pro-inflammatory cytokine generation following ischemic brain injury. It is possible that activation of the TLR pathway is the initial response to human ischemic stroke and peripheral tolerance plays a role in modulating the cerebral ischemic response through TLRs and adaptive immune mechanisms.

AAN.com: What are the barriers to doing this type of genetics study in the acute setting?

Barr: This study was hard to implement because in the emergency department (ED) setting patient care takes priority. We spent months designing and implementing pilot studies in the laboratory as well as the ED to determine the best strategy. I became a member of the NIH Stroke Team and responded to all stroke pages during day-time hours to obtain consent prior to research blood draws. Anyone who has tried to obtain consent from a patient or surrogate in the ED knows how difficult this can be; you must quickly establish rapport and trust with the patient or surrogate and describe the study in lay terms quickly and efficiently. Effective communication between nurses, physicians, and laboratory technicians is necessary to ensure the blood draw is done on time, and the specimen must be processed on-site.

AAN.com: What are the clinical implications of your findings?

Barr: Our study confirms that gene expression profiling can be used to characterize ischemic stroke in the acute setting. It is too early, however, to talk about direct clinical implications. We have to validate the gene panel against other disorders that mimic stroke in the ED setting. If the expression of this panel of genes is validated, a point of care diagnostic test can be developed to monitor the expression of these genes. For this purpose, we are planning a larger study at West Virginia University in Morgantown, West Virginia, and the Mayo Clinic in Jacksonville, Florida.

In addition, the TLR pathway is a promising target for therapeutic stroke intervention. We are collaborating with basic scientists at WVU to determine the functional significance of the 9-gene panel and how best to target the TLR pathway post-stroke.

Because the majority of genes that we identified are related to vascular function, it is possible, therefore, that these genes are markers of ischemic stroke risk. If this is the case (and future studies must look into this possibility), the expression of these genes could be used in the primary care setting to monitor cardiovascular disease status and response to therapeutics.

An extremely interesting potential application of these findings is prognosis of outcome. Follow-up work in our laboratory suggests the change in the expression of these genes over time may identify those at risk for poor outcome after stroke. If future studies confirm this, the gene panel may be used to monitor patients at high risk for complications post-stroke.

Disclosures:

Dr. Barr has received research support from the NIH/NINR Graduate Partnership Program Pre-Doctoral Fellowship award.

Dr. Merino performed a one-time consultation with staff from Bell, Falla and Associates.

He is a member of the Stroke Publishing Technology Committee for the journal Stroke and was a member of the editorial board of Stroke from 2008-2010.

Dr. Merino has received research support from the cost reimbursement contract between NIH/NINDS Intramural Program and Suburban Hospital to support the clinical, administrative, and technical activities of the NIH Stroke Program at Suburban Hospital. He is also stroke adjudicator for the Women's Health Initiative at NIH.